SemEval 2022 Task 12: Symlink - Linking Mathematical Symbols to their Descriptions

Viet Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Nguyen


Abstract
We describe Symlink, a SemEval shared task of extracting mathematical symbols and their descriptions from LaTeX source of scientific documents. This is a new task in SemEval 2022, which attracted 180 individual registrations and 59 final submissions from 7 participant teams. We expect the data developed for this task and the findings reported to be valuable for the scientific knowledge extraction and automated knowledge base construction communities. The data used in this task is publicly accessible at https://github.com/nlp-oregon/symlink.
Anthology ID:
2022.semeval-1.230
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1671–1678
Language:
URL:
https://aclanthology.org/2022.semeval-1.230
DOI:
10.18653/v1/2022.semeval-1.230
Bibkey:
Cite (ACL):
Viet Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, and Thien Nguyen. 2022. SemEval 2022 Task 12: Symlink - Linking Mathematical Symbols to their Descriptions. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1671–1678, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
SemEval 2022 Task 12: Symlink - Linking Mathematical Symbols to their Descriptions (Lai et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.230.pdf